Many applications for mobile devices benefit from knowing the approximate physical location of the mobile device. For example, a map application on a wireless phone may give driving directions to a specific location from the current location of the device. Often, these devices use more than one signal type to determine the approximate physical location of the device. For example, a cellular phone may use global positioning system (GPS) signals, WiFi signals, and/or cellular signals.
When a device uses wireless signals to estimate a location of the device, typically the device (or something communicating with the device) uses triangulation to determine the location. If the location of three or more things is known, and the distance from the device to each of those things is known, the location of the device may be determined. For example, if a cellular telephone knows the approximate distance to each of three base stations and the approximate location of each of those base stations, the cellular phone may determine its approximate location.
Typically, cellular phones determine the distance from a base station to the cellular phone by timing the arrival of a reference signal. However, wireless signals interact with things in the physical environment such as buildings. As a result, wireless signals typically travel over several different paths before arriving at the receiver. In other words, the receiver actually sees more than one version of the same signal, where the different versions vary in attenuation, delay, and phase (i.e., fading or delay-spread). As the physical environment between the transmitter and the receiver changes (e.g., the wireless device is moving), the amount of delay-spread varies.
Accordingly, time of arrival estimation techniques typically programmed into devices make certain assumptions about the amount of delay-spread that is likely to occur. However, if the time of arrival estimation technique assumes a delay-spread channel when the channel is not a delay-spread channel (or vice versa), the time of arrival estimation will be less accurate. This in turn causes the location estimation to be less accurate.